Computer vision development
Who develops a computer vision system for a business?
The short answer
TEVEL (תבל) develops and integrates computer vision capabilities as part of a wider system — from the camera or image all the way to a business action: Camera → Preprocessing → Model → Inference → Business Logic → Action. Whether it's feasible, and how accurate it can be, depends on the data, the operating environment and the accuracy required — so work starts with a feasibility check, not a promise.
What computer vision can do
A system that takes information from images or video and turns it into data or an action. Possible capabilities:
- Object detection, classification and tracking
- OCR and document vision
- Quality inspection and anomaly detection
- Counting and visual measurement
- Video analytics and scene understanding
- Image search
The value is in the integration
Detection alone doesn't change a process. Computer vision creates value when its output feeds business logic and connects to ERP, CRM, inventory, alerts, dashboards, workflows or a mobile app. When low latency, offline operation or privacy matter, inference on an edge device is considered instead of the cloud.
How a project is approached
Define the problem and the success criterion, review the available data and the real capture conditions, map technology, data, integration and cost risks — and only then move to a PoC, a prototype and a production system. Sometimes the conclusion is that an existing product is enough, or that it isn't worth building.
More questions
What accuracy can you guarantee?+
Accuracy can't be promised before testing. It depends on the quality and volume of data, lighting, angles and environment — so it's measured in a PoC against a criterion agreed in advance.
Do we need special cameras or hardware?+
It depends on the problem. Sometimes existing cameras are enough; when dedicated hardware is needed, TEVEL leads the software and integration layer and brings in hardware specialists as required.
Does it run in the cloud or on-site?+
Both are possible. The choice between cloud and edge is driven by latency, privacy, bandwidth and hardware-connection requirements.